DocumentCode :
2008987
Title :
Artificial Neural Network for real time modelling of photovoltaic system under partial shading
Author :
Di Vincenzo, Maria Carla ; Infield, David
Author_Institution :
Inst. for Energy & Environ., Strathclyde Univ., Glasgow, UK
fYear :
2010
fDate :
6-9 Dec. 2010
Firstpage :
1
Lastpage :
5
Abstract :
Shading caused by surrounding objects is an important issue for solar energy system design and analysis. In the special case of building integrated photovoltaic (BIPV) systems, the prediction of the partial shading is critical in order to reduce losses due to poor Maximum Power Point Tracking (MPPT). This paper will present a technique that uses Artificial Neural Network to predict the output power from a photovoltaic array in case of partial shading.
Keywords :
building integrated photovoltaics; maximum power point trackers; neural nets; power engineering computing; artificial neural network; building integrated photovoltaics; maximum power point tracking; partial shading; Arrays; Artificial neural networks; Biological system modeling; Buildings; Photovoltaic systems; Power measurement; SPICE;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Sustainable Energy Technologies (ICSET), 2010 IEEE International Conference on
Conference_Location :
Kandy
Print_ISBN :
978-1-4244-7192-8
Type :
conf
DOI :
10.1109/ICSET.2010.5684464
Filename :
5684464
Link To Document :
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